Evaluation of the relation between subclinical systolic dysfunction defined by four-dimensional speckle-tracking echocardiography and growth differentiation factor-15 levels in patients with acromegaly.

PURPOSE: In patients with acromegaly, the long-term presence of elevated GH and IGF-1 levels is associated with an unfavorable cardiovascular risk profile. We aimed to assess the relationship of four-dimensional speckle tracking echocardiographic (4DSTE) measurements with growth differentiation factor-15 (GDF-15) levels and the Framingham Cardiovascular Risk Score (FRS) in patients with acromegaly. METHODS: A single-center, cross-sectional study was conducted. The study included 40 acromegaly and 32 age- and gender-matched controls. Anthropometric, biochemical, and echocardiographic assessments were performed. GDF-15 levels were measured using ELISA. RESULTS: In the controlled acromegaly group, global longitudinal (GLS), circumferential (GCS), area (GAS), and radial (GRS) strain measurements identified by 4DSTE were lower than those of the controls (p < 0.05). Moreover, strain parameters were lower in active acromegaly patients than in controls, but the difference was not statistically significant. The GLS was negatively correlated with age, the estimated disease duration, and FRS. Serum GDF-15 levels showed no significant difference between the acromegaly and control groups. In patients with acromegaly, serum GDF-15 levels were positively correlated with age, waist-to-hip ratio, systolic and diastolic blood pressure, FRS, fasting plasma glucose, and HbA1c, but not with strain parameters. The multiple regression analysis revealed that FRS was an independent factor associated with serum GDF-15 levels in patients with acromegaly and the overall cohort (p < 0.001). CONCLUSION: Our study demonstrates that while LVEF was within normal limits, global strain parameters (GLS, GCS, GAS, and GRS) measured by using a novel imaging technique, 4DSTE, were lower in patients with acromegaly, suggesting the presence of subclinical systolic dysfunction in patients with acromegaly. GDF-15 can be a potential predictor of cardiovascular risk in patients with acromegaly.

The Clinical Characteristics and Outcomes of COVID-19 Patients with Pre-Existing Thyroid Dysfunction: A Nationwide Study.

To which extent the pre-existing hypothyroidism or hyperthyroidism has an impact on coronavirus infection 2019 (COVID-19) outcomes remains unclear. The objective of this study was to evaluate COVID-19 morbidity and mortality in patients with pre-existing thyroid dysfunction. A retrospective cohort of patients with a polymerase chain reaction (PCR)-confirmed COVID-19 infection (n=14 966) from March 11 to May 30, 2020, was established using the database of the Turkish Ministry of Health. We compared the morbidity and mortality rates of COVID-19 patients with pre-existing hypothyroidism (n=8813) and hyperthyroidism (n=1822) to those patients with normal thyroid function (n=4331). Univariate and multivariate regression analyses were performed to identify the factors associated with mortality. Mortality rates were higher in patients with hyperthyroidism (7.7%) and hypothyroidism (4.4%) than those with normal thyroid function (3.4%) (p<0.001 and p=0.008, respectively). Pre-existing hyperthyroidism was significantly associated with an increased risk of mortality (OR 1.54; 95% CI, 1.02-2.33; p=0.042) along with advanced age, male gender, lymphopenia and chronic kidney disease (p<0.001 for all). Although a potential trend was noted, the association between pre-existing hypothyroidism and mortality was not significant (OR 1.36; 95% CI, 0.99-1.86; p=0.055). In conclusion, this study showed an association between pre-existing hyperthyroidism with higher COVID-19 mortality. A potential trend towards increased mortality was also observed for hypothyroidism. The risk was more pronounced in patients with hyperthyroidism.

Giant growth hormone-secreting pituitary adenomas from the endocrinologist's perspective.

OBJECTIVES: Since giant (≥40 mm) GH-secreting pituitary adenomas are rarely encountered, data on their characteristics and treatment outcomes are limited. We aimed to investigate the characteristics of giant GH-secreting pituitary adenomas and to compare their clinical, biochemical, imaging and histopathological features with non-giant macroadenomas. MATERIALS AND METHODS: We have evaluated 15 (six female/nine male) and 57 (29 female/28 male) patients with acromegaly in giant and <40 mm adenoma groups, respectively. Patients with <40 mm adenoma were further divided into subgroups with adenoma size 20-29 mm and 30-39 mm. RESULTS: In giant adenoma group, median (IQR) preoperative maximal diameter of adenoma was 40 mm (5 mm), median preoperative GH level was 40 (153.4) ng/mL and median baseline IGF-1 level was 2.19 (1.88) × ULN for age and sex. The number of surgeries was significantly higher in giant adenoma group (median 2, IQR 2) in which 66.7% of patients underwent repeated surgeries (p = 0.014). Residual tumor was detected after last operation in all patients with giant adenoma. Total number of treatment modalities administered postoperatively increased as adenoma size increased (p = 0.043). After a median follow-up duration of 10 years (IQR 10), hormonal remission was achieved in six patients (40%) of giant adenoma group, while the rate of hormonal remission in non-giant adenoma group was 37%. Although preoperative GH and IGF-1 levels and Ki-67 index tended to be higher with increasing adenoma size, there was no statistically significant difference between groups in terms of these variables, as well as age, sex and invasion status. CONCLUSION: Hormonal remission rates of acromegaly patients with ≥20 mm pituitary macroadenoma were comparable. However, giant GH-secreting pituitary adenomas require an aggressive multimodal treatment approach.

Follow, consider, and catch: second primary tumors in acromegaly patients.

BACKGROUND AND AIM: The risk of second primary tumors is increased in general cancer population, however, there is no data on acromegalic cancer patients in this regard. The aim of this study is to determine the prevalence of patients with two primary tumors among acromegalic cancer patients and to evaluate if patients with two primaries have distinct clinical characteristics or risk factors compared to those with one. METHODS: This is a single-center retrospective cohort study. The study included 63 patients with at least one malignant tumor out of a total number of 394 acromegaly patients. Patients with multiple primary neoplasms were evaluated in detail. RESULTS: This study revealed a 16% cancer prevalence in acromegaly patients, with 14% (9/63) having two primary neoplasms. Papillary thyroid carcinoma was the most prevalent tumor in the entire cancer cohort (41%, 26/63), and in the group of patients with two primaries (44%, 4/9). Patients with two primary tumors were older than those with one when diagnosed with acromegaly (48.3 ± 16.6 vs. 43.3 ± 10.7 years), which might be attributed to a longer diagnostic delay (median of 4.5 vs. 2 years). The period between the onset of acromegaly symptoms and diagnosis was not associated with earlier cancer diagnosis. No relationship between circulating GH or IGF-I levels and the number of neoplasms was found. CONCLUSION: The development of second primary tumors in acromegalic patients with cancer diagnosis is not rare. Acromegalic cancer patients should be closely monitored for new symptoms or signs that could be associated with second primary tumors.

Energy expenditure and glucose-lowering effect of different exercise modalities in diabetes mellitus.

OBJECTIVES: Hypoglycaemia is a serious complication of exercise in patients with type 2 diabetes mellitus (T2DM). The aim of this study was to test energy expenditure and the degree of the glucose-lowering effect of different exercise modalities. DESIGN: Cross-sectional study PARTICIPANTS: This study included 44 patients {35 women and nine men, mean age 51 [standard deviation (SD) 5] years} with T2DM [mean HbA1c 7% (SD 1%)]. MAIN OUTCOME MEASURES: Standardised exercise tests for walking, running and cycling were performed using the 6-minute walk test (6MWT), incremental shuttle walk test (ISWT), and symptom-limited maximal cycle exercise test, respectively. Energy expenditure was assessed with a multisensory accelerometer. Change in capillary glucose levels (∆glucose) was measured before and after each exercise modality. RESULTS: ∆Glucose was lower in the 6MWT {median 14 [interquartile range (IQR) 22] mg/dl} than in the ISWT [median 18 (IQR 23) mg/dl; median difference 7 mg/dl, 95% confidence interval (CI) of the difference 3-11] and the cycle test [median 18 (IQR 24) mg/dl; median difference 7 mg/dl, 95% CI 0-16]. Energy expenditure was lower during the 6MWT [median 41 (IQR 18) Kcal] compared with the ISWT [median 51 (IQR 23) Kcal; median difference 11 Kcal, 95% CI 6-16] and the cycle test [median 44 (IQR 25) Kcal; median difference 6 Kcal, 95% CI 0-13]. CONCLUSIONS: Energy expenditure and corresponding glucose-lowering effect during exercise in patients with T2DM can be predicted from the results of an exercise test. The type of exercise is related to the risk of hypoglycaemia. Walking is associated with the lowest energy expenditure and risk of hypoglycaemia, while cycling and running/jogging cause higher energy expenditure and greater reductions in glucose in patients with T2DM. CONTRIBUTION OF THE PAPER.

Reduced irisin levels in patients with acromegaly.

OBJECTIVES: Several metabolic disturbances are seen in acromegaly however, data regarding the contribution of irisin to these disturbances is currently insufficient. In a cohort of patients with acromegaly, we measured serum irisin levels in active and controlled cases and determined independent factors that effect serum irisin including fibronectin type III domain-containing protein 5 (FNDC5) genotyping. METHODS: A cross-sectional case-control study including 46 patients with acromegaly (28 F/18 M, age: 50.3 ± 12.1 year, BMI: 30.7 ± 5.1 kg/m2) and 81 age-, gender-, body mass index- and body composition-matched healthy controls was conducted. 15 acromegalic patients (33%) had active disease. Irisin levels were measured by enzyme-linked immunosorbent assay. Three different regions (rs3480, rs1746661, and rs16835198) of FNDC5 were subjected to polymorphism analyses. RESULTS: Both groups were overweight and had similar body composition. Irisin levels were lower in patients with acromegaly than controls (median [IQR]: 44.8 [41.7-46.7] ng/mL vs. 51.7 [45.5-60.1] ng/mL, p≤0.001, respectively). Active and controlled patients had similar irisin levels. Irisin was not correlated with growth hormone (GH), insulin-like growth factor 1 (IGF-1), and IGF-1 index. In multiple linear regression model, somatostatin receptor ligand use (ß=-20.30, 95% CI [-34]-[-6], p=0.006) was determined as the only independent factor that affect serum irisin. CONCLUSIONS: Serum irisin levels are low in patients with acromegaly who are on somatostatin receptor ligand therapy. Single nucleotide polymorphisms (SNPs) of FNDC5 have no independent effects on circulating irisin levels under somatostatin ligand action. Endocrine muscle functions also seem to be regulated by somatostatin action, which requires further studies.

Discrimination between non-functioning pituitary adenomas and hypophysitis using machine learning methods based on magnetic resonance imaging­derived texture features.

PURPOSE: Hypophysitis is a heterogeneous condition that includes inflammation of the pituitary gland and infundibulum, and it can cause symptoms related to mass effects and hormonal deficiencies. We aimed to evaluate the potential role of machine learning methods in differentiating hypophysitis from non-functioning pituitary adenomas. METHODS: The radiomic parameters obtained from T1A-C images were used. Among the radiomic parameters, parameters capable of distinguishing between hypophysitis and non-functioning pituitary adenomas were selected. In order to avoid the effects of confounding factors and to improve the performance of the classifiers, parameters with high correlation with each other were eliminated. Machine learning algorithms were performed with the combination of gray-level run-length matrix-low gray level run emphasis, gray-level co-occurrence matrix-correlation, and gray-level co-occurrence entropy. RESULTS: A total of 34 patients were included, 17 of whom had hypophysitis and 17 had non-functioning pituitary adenomas. Among the 38 radiomics parameters obtained from post-contrast T1-weighted images, 10 tissue features that could differentiate the lesions were selected. Machine learning algorithms were performed using three selected parameters; gray level run length matrix-low gray level run emphasis, gray-level co-occurrence matrix-correlation, and gray level co-occurrence entropy. Error matrices were calculated by using the machine learning algorithm and it was seen that support vector machines showed the best performance in distinguishing the two lesion types. CONCLUSIONS: Our analysis reported that support vector machines showed the best performance in distinguishing hypophysitis from non-functioning pituitary adenomas, emphasizing the importance of machine learning in differentiating the two lesions.

Higher rate of COVID-19 mortality in patients with type 1 than type 2 diabetes: a nationwide study.

INTRODUCTION: COVID-19 disease has a worse prognosis in patients with diabetes, but comparative data about the course of COVID-19 in patients with type 1 (T1DM) and type 2 diabetes (T2DM) are lacking. The purpose of this study was to find out the relative clinical severity and mortality of COVID-19 patients with T1DM and T2DM. MATERIAL AND METHODS: A nationwide retrospective cohort of patients with confirmed (PCR positive) COVID-19 infection (n = 149,671) was investigated. After exclusion of individuals with unspecified diabetes status, the adverse outcomes between patients with T1DM (n = 163), T2DM (n = 33,478) and those without diabetes (n = 115,108) were compared by using the propensity score matching method. The outcomes were hospitalization, the composite of intensive care unit (ICU) admission and/or mechanical ventilation, and mortality. RESULTS: The patients with T1DM had higher mortality than the age- and gender-matched patients with T2DM (n = 489) and those without diabetes (n = 489) (p < 0.001). After further adjustment for the HbA1c, and microvascular and macrovascular complications, the odds of mortality (OR: 3.35, 95% CI: 1.41-7.96, p = 0.006) and ICU admission and/or mechanical ventilation (OR: 2.95, 95% CI: 1.28-6.77, p = 0.011) were significantly higher in patients with T1DM compared to those with T2DM. Older age (OR: 1.06, 95% CI: 1.01-1.12, p = 0.028) and lymphopaenia (OR: 5.13, 95% CI: 1.04-25.5, p = 0.045) were independently associated with mortality in patients with T1DM. CONCLUSIONS: Patients with T1DM had worse prognosis of COVID-19 compared to T2DM patients or those without diabetes. These cases should be cared for diligently until more data become available about the causes of increased COVID-19 mortality in T1DM.

Clinical Characteristics and Outcomes of COVID-19 Patients with Overweight and Obesity: Turkish Nationwide Cohort Study (TurCObesity).

PURPOSE: While obesity is related to more severe outcomes of coronavirus disease 2019 (COVID-19), factors leading to poor prognosis still remain unclear. The present study evaluated the outcomes of COVID-19 patients who were overweight or obese and variables associated with severe disease in a large group of consecutive cases. METHODS: A nationwide retrospective cohort study was performed using the Turkish National Healthcare Database. Demographic characteristics, laboratory tests, comorbidities, and medications of patients registered between March 11 and May 30, 2020, were recorded. RESULTS: A total of 14, 625 patients (median age:42, IQR:26 years; female 57.4%) with normal weight (34.7%), overweight (35.6%), and obesity (29.7%) were included. Hospitalization, ICU admission, intubation/mechanical ventilation, pulmonary involvement, and mortality were significantly higher in patients who were overweight or obese. In adjusted analyses, both overweight (OR, 95% CI: 1.82, 1.04-3.21; p=0.037) and obesity (OR, 95% CI: 2.69, 1.02-1.05; p<0.001) were associated with a higher intubation/mechanical ventilation rate but only obesity was associated with increased mortality (OR, 95% CI: 2.56, 1.40-4.67; p=0.002). Old age, male gender, chronic kidney disease, and high C reactive protein levels were independently associated with COVID-19 mortality in overweight or obese patients. CONCLUSIONS: COVID-19 patients who were overweight or obese were more likely to have adverse outcomes but only obesity was a predictor of mortality. Such patients should receive urgent medical attention and active management, especially the elderly, men, and people with chronic kidney disease.

No association of Gaucher disease with COVID-19-related outcomes: a nationwide cohort study.

BACKGROUND: It is well documented that patients with chronic metabolic diseases, such as diabetes and obesity, are adversely affected by the COVID-19 pandemic. However, when the subject is rare metabolic diseases, there are not enough data in the literature. AIM: To investigate the course of COVID-19 among patients with Gaucher disease (GD), the most common lysosomal storage disease. METHODS: Based on the National Health System data, a retrospective cohort of patients with confirmed (polymerase chain reactionpositive) COVID-19 infection (n = 149 618) was investigated. The adverse outcomes between patients with GD (n = 39) and those without GD (n = 149 579) were compared with crude and propensity score-matched (PSM) groups. The outcomes were hospitalisation, the composite of intensive care unit (ICU) admission and/or mechanical ventilation and mortality. RESULTS: The patients with GD were significantly older and had a higher frequency of hypertension (HT), Type 2 diabetes mellitus (T2DM), dyslipidaemia, asthma or chronic obstructive pulmonary disease, chronic kidney disease, coronary artery disease, heart failure and cancer. Although hospitalisation rates in Gaucher patients were found to be higher in crude analyses, the PSM models (model 1, age and gender matched; model 2, matched for age, gender, HT, T2DM and cancer) revealed no difference for the outcomes between patients with GD and the general population. According to multivariate regression analyses, having a diagnosis of GD was not a significant predictor for hospitalisation (P = 0.241), ICU admission/mechanical ventilation (P = 0.403) or mortality (P = 0.231). CONCLUSION: According to our national data, SARS-CoV-2 infection in patients with GD does not have a more severe course than the normal population.